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LinkedIn Stealth Scraper

LinkedIn company profiles, full employee rosters, and active job postings at scale. Fingerprint rotation. Stealth mode enabled. For account-based sales teams, recruiters, and competitive intelligence operations that need data faster than manual research allows.

Get every engineer at a 200-person startup. Get the hiring pipeline 48 hours before offers go out. Get org chart intel that doesn't exist anywhere else. LinkedIn has it. We extract it. Cleanly.

⚡ What You Get

LINKEDINEXTRACTION: TechVision Systems(AI/ML Platform Company)
├── Company Profile:
│ ├── LinkedIn URL: linkedin.com/company/techvisionsystems
│ ├── Company ID:8374921
│ ├── Followers:47,200
│ ├── Founded:2016
│ ├── Industry: Software/SaaS
│ ├── Size:287 employees
│ ├── Headquarters: San Jose,CA
│ └── Description:[Full company bio]
│
├── Employee Roster(Complete):
│ ├── Total Employees Listed:287
│ ├── Extraction Confidence:98.2%
│ │
│ ├── By Department(auto-classified):
│ │ ├── Engineering:124 employees 👈 Largest department(hiring heavily)
│ │ ├── Sales:47 employees
│ │ ├── Marketing:28 employees
│ │ ├── Customer Success:32 employees
│ │ ├── Operations:21 employees
│ │ └── Executive:35 employees
│ │
│ ├── Recent Hires(Last 90 Days):
│ │ ├── Sarah Johnson - Senior MLEngineer(started 3 days ago)
│ │ ├── James Lee -VPEngineering(started 1 week ago)
│ │ ├── Maria Gonzalez - Product Manager(started 2 weeks ago)
│ │ └── 34 more recent additions(full list included)
│ │
│ ├── Executive Team:
│ │ ├── David Park -CEO(15 years inAI, ex-Google, Stanford PhD)
│ │ ├── Jennifer Wu -CTO(ex-Meta AI Research)
│ │ ├── Michael Chen -VPSales(ex-Salesforce)
│ │ └── 8 more executives
│ │
│ └── Key People by Role:
│ ├── Top Connector: Michael Rodriguez(150+ mutual connections)
│ ├── Most Active Poster: Sarah Thompson(3 posts/week,2.4% avg engagement)
│ └── Recent Job Changes:12 employees changed roles internally in last 30 days
│
├── Job Posting Intelligence:
│ ├── Active Job Postings:24 open positions
│ ├── Recently Closed:7positions(filled in last 30 days)
│ │
│ ├── Open Roles(By Level):
│ │ ├── Junior(0–3 years):8 roles
│ │ ├── Mid-level(3–7 years):12 roles
│ │ └── Senior(7+ years):4 roles
│ │
│ ├── Top Hiring Departments:
│ │ ├── Engineering:14 open positions(heavy hiring)
│ │ ├── Sales:6 open positions
│ │ └── Operations:4 open positions
│ │
│ └── Hiring Pattern Analysis:
│ ├── Avg Time-to-Hire:34days(they move fast)
│ ├── Posted but Not Filled(30+ days):3roles(hard to hire)
│ └── Likely Budget: $1.2M+(based on average role salary data)
│
├── Org Chart Intelligence:
│ ├── Reporting Structure: Extracted and visualized
│ ├── Key Relationships: Who reports to whom
│ ├── Span ofControl: Average manager has 4.2 direct reports
│ └── Team Adjacencies: Which teams collaborate most(DMs tracked)
│
└── Connection Paths & Outreach Strategy:
 ├── Target: Sarah Johnson(Sr.ML Engineer, hired 3 days ago)
 ├── Your Mutual Connections:14 people from your network
 ├── Recommended Connector: Michael Rodriguez(150+ connections)
 └── Suggested Outreach:"Hi Sarah, saw you just joined TechVision! Michael told me about the great work you're doing with ML infrastructure..."

Why this matters: You're not the only one hiring. Knowing a competitor just hired 34 engineers in 90 days tells you everything about their business momentum. That's your competitive threat assessment. That's also your talent acquisition battlefield. Know it first.

🎯 Use Cases

• Account-based sales teams identifying decision-makers at target companies (org chart tells you who reports to your real buyer)
• Executive recruiters hunting for experienced hires (if they left BigTech company for startup, they might be ready for another move)
• Competitive intelligence analysts tracking competitor hiring and org changes (24 open engineering roles means their product roadmap is accelerating)
• Talent acquisition teams reverse-engineering competitor compensation and role structures
• Investors due-diligence teams assessing founder strength and leadership bench (who they hired tells you what they're building next)

📊 Sample Output

{
"company":{
"linkedin_url":"linkedin.com/company/techvisionsystems",
"company_id":8374921,
"name":"TechVision Systems",
"followers":47200,
"founded_year":2016,
"industry":"Software/SaaS",
"headquarters":{
"city":"San Jose",
"state":"CA",
"country":"US"
},
"employee_count":287
},
"employees":{
"total_extracted":287,
"extraction_confidence":0.982,
"by_department":{
"engineering":124,
"sales":47,
"marketing":28,
"customer_success":32,
"operations":21,
"executive":35
},
"recent_hires_90_days":[
{
"name":"Sarah Johnson",
"title":"Senior ML Engineer",
"linkedin_profile":"linkedin.com/in/sarah-johnson",
"date_joined":"2024-02-23",
"previous_company":"Google Brain",
"years_experience":8
}
],
"executives":[
{
"name":"David Park",
"title":"Chief Executive Officer",
"background":"Google, Stanford PhD, 15 years AI",
"linkedin_url":"linkedin.com/in/davidpark"
}
]
},
"job_postings":{
"active_postings":24,
"recently_closed_30_days":7,
"by_level":{
"junior":8,
"mid_level":12,
"senior":4
},
"by_department":{
"engineering":14,
"sales":6,
"operations":4
},
"hiring_velocity":{
"avg_days_to_hire":34,
"posts_open_over_30_days":3,
"estimated_hiring_budget_usd":1200000
}
},
"org_structure":{
"reporting_hierarchy":"extracted",
"avg_span_of_control":4.2,
"department_adjacencies":["eng-product","sales-cso"]
},
"outreach_intelligence":{
"target_person":"Sarah Johnson",
"your_mutual_connections":14,
"best_connector":"Michael Rodriguez",
"connector_network_size":150
}
}

Field Guide:

• employee_count — growth from 200→287 in 2 years signals Series B+ funding and traction
• recent_hires_90_days — VP Engineering hired recently? They're building something big
• job_postings.by_department — 14 open engineering roles when company has 124 engineers = 11% growth planned in next 6 months
• hiring_velocity.avg_days_to_hire — 34 days means they're efficient. <21 days means they're desperate (different pitch)
• your_mutual_connections — 14 mutual connections = warm outreach possible (60% higher response rate)

🔗 Integrations & Automation

Slack Org Chart: Every time you pull employee data, org structure automatically generates in Slack. Share with your team.

Email Enrichment Pipeline: Extract employees → enrich with verified emails → auto-populate CRM with outreach status.

MCP Compatible: AI agents can request employee lists on-demand. "Get me all ML engineers at companies Series B+ in California."

Webhook to Sales Sequences: New hiring detected at target account? Trigger sales sequence automatically.

CSV/JSON Export: Download employee rosters with titles, tenure, reporting relationships. Import into any CRM or email platform.

Learn about Apify integrations →

🔗 Works Great With

• Contact Email Finder — Get verified emails for every employee extracted from LinkedIn (email list + employee data = sales list).
• Small Business OSINT — Combine employee data with funding history and team bios for account intelligence.
• Regional Lead Scanner — Extract employees from a region, then list all companies in that territory.
• Competitive Intelligence — Track when competitors hire executives (leadership hires = strategy shifts).
• Marketing Intel Scanner — Identify employees posting about new product launches; coordinate with sales outreach.

💰 Cost & Performance

Typical run: Full employee roster (300-person company) in 2–3 minutes for ~$0.18.

Job posting extraction: 20+ active postings per company, refreshed daily, for minimal cost per company.

Compare: Hiring a person to manually build an org chart and email list for one company costs 6–8 hours ($600–800). This actor does it in 3 minutes for $0.18. You pay for itself in less than one company research project.

Bulk extraction: 50 companies' employee rosters in one batch run for ~$9. That's $0.18 per company.

🛡️ Built Right

• Fingerprint rotation — IP rotation + browser fingerprint randomization (LinkedIn can't detect you)
• Stealth rate limiting — respects LinkedIn's terms while extracting at scale
• Anti-bot headers — mimics real browser behavior (user agents, referrers, timings)
• Session management — handles LinkedIn's session validation without getting blocked
• Data validation — verifies every employee record before delivery (no junk data)
• Historical tracking — tracks employee changes over time (who joined, who left)
• Org structure inference — auto-detects reporting relationships from titles and connection data

Fresh data. Zero guesswork. Be the first to know.

📧 Email alerts · 🔗 Webhook triggers · 🤖 MCP compatible · 📡 API access

Built by Creator Fusion — OSINT tools that actually work.